KR102066330B1 - A method and device for determining a category directory, and an automatic classification method and device - Google Patents

Abstract

The present application discloses a method and device for determining a category directory, and an automatic classification method and device. The method for determining a category directory may include determining a first category directory based on a first preset correspondence, receiving a category change message from a user, and generating a category change item including category change contents. Determining a statistical start time associated with a first category identifier (ID) included in the category change item, and determining a first time interval associated with the first category ID based on the statistical start time; Statistically analyzing a category change item generated within and including the first category ID to obtain a first statistical analysis result, and when the first statistical analysis result satisfies the first preset rule, the first correspondence relationship. A second category containing a second correspondence by modifying a first category directory comprising a Obtaining a logical directory and setting the second category directory as the default category directory. Use of this application will improve the accuracy of the classification of resource processing records.

Description

A method and device for determining a category directory, and a method and device for automatic classification {A METHOD AND DEVICE FOR DETERMINING A CATEGORY DIRECTORY, AND AN AUTOMATIC CLASSIFICATION METHOD AND DEVICE}

TECHNICAL FIELD The present application relates to the technical field of computer processing, and more particularly, to a method and device for determining a category directory, and an automatic classification method and device.

In the technical field of computer processing, when completing resource processing, the resource processing system generally generates a record describing the resource processing process. Such resource processing records may generally include user information, processing side information, resource amount, resource processing time, and the like. Such resource processing records may be classified into a number of categories to facilitate statistical analysis of records by the user, and the like.

An existing method for determining a category directory includes using processing side information in a resource processing record as a category name in a category directory, and grouping all records having the same processing side information into the same category under that category name; The category directory contains all category names for each category.

In the process of preparing the present application, the existing technology includes a problem that the processing side information included in the resource processing record generated by the resource processing system may be changed since the resource processing system may include a plurality of subsystems. Was identified. Thus, using existing category classification techniques, resource processing records that are assumed to be classified into the same category can actually be classified into many different categories. As a result, the generated category directory may not reflect the correct classification result.

An embodiment of the present application aims to provide a method and device for determining a category directory, and an automatic classification method and device in order to improve the accuracy of classification of resource processing records.

In particular, to solve the above technical problem, an embodiment of the present application provides a method and device for determining a category directory, and an automatic classification method and device.

A method for determining a category directory includes determining a first category directory based on processing side information of a resource processing record and a first predetermined correspondence between the processing side information and a category, and receiving a category change message from a user. Generating a category change item, the category change item including a category change indicating that the user changes a first category having a first category ID to a second category having a second category ID; Determining a statistical start time associated with the first category ID that has been generated, and determining a first time interval associated with the first category ID; and a category generated within the first time interval and including the first category ID. Statistically analyze the changes to obtain the first statistical analysis And, if the first statistical analysis result satisfies a first preset rule, the first category directory including the first correspondence including a second correspondence between the processing side information and a category. Modifying to a second category directory and setting the second category directory as the default category directory; and if the first statistical analysis result does not satisfy the first preset rule, the first category directory as the default category directory. Setting as.

An automatic classification method for classifying resource processing records based on a category directory determined using a category directory determining method includes: receiving resource processing records from a user, and performing a process between a category included in a default category directory and the processing side information. Classifying the resource processing record using a correspondence relationship to obtain a classification result, and returning the classification result to a user.

The category directory determination device includes a first category directory determination unit, a category change item generation unit, a first time interval determination unit, a first statistical analysis unit, and a default category directory determination unit. The first category directory determination unit is operable to determine a first category directory based on processing side information of a resource processing record and a first predetermined correspondence relationship between the processing side information and a category, wherein the category change item generating unit Is operable to receive a category change message from the user and generate a category change item including category change contents indicating that the first category having the first category ID is changed to the second category having the second category ID; The first time interval determining unit is operable to determine a statistical start time associated with the first category ID included in the category change item, and determine a first time interval associated with the first category ID, The first statistical analysis unit is generated within the first time interval and the first Statistically analyzing a category change item including a category ID to obtain a first statistical analysis result, wherein the default category directory determining unit is configured to generate a first statistical analysis result when the first statistical analysis result satisfies a first preset rule; Change a first category directory including a first correspondence to a second category directory including a second correspondence between the processing side information and a category, and set the second category directory as a default category directory, and the first statistical directory If the analysis result does not satisfy the first preset rule, it is operable to set the first category directory as a default category directory.

The automatic classification device includes a receiving unit, a default category classification unit and a feedback unit, the receiving unit being operable to receive a resource processing record from a user, wherein the default category classification unit is a category and a process included in the default category directory. And classifying the resource processing record using a second correspondence between side information to obtain a classification result, and the feedback unit is operable to return the classification result to the user.

 As illustrated by the technical solution of an implementation embodiment, the disclosed method and device for determining a category directory analyzes processing side information to determine a correspondence between processing side information and a category. Thus, similar resource processing records will correspond to the same category, thereby improving the accuracy of the classification result. On the other hand, a user message for changing the category is received, and the existing category directory is updated based on the user category change message to ensure that the determined category directory meets the needs of the user, so that the accuracy of the classification result is further improved. The automatic classification method and device classify the resource processing record using the result obtained through the category directory determination method and the device. Thus, the accuracy of the obtained classification result is improved. In addition, by performing classification according to the continuously updated category directory, the classification result can better meet the classification requirements of the user.

BRIEF DESCRIPTION OF DRAWINGS To describe the technical solutions in the embodiments of the present application and / or in the existing technology more clearly, the accompanying drawings are briefly described herein. Apparently, the accompanying drawings described herein merely show some exemplary embodiments of the present application, and those skilled in the art may further derive other drawings from these accompanying drawings without creative efforts.
1 shows a flowchart of a first embodiment of a method for determining a category directory according to the present application.
2 shows a flowchart of a second embodiment of a method for determining a category directory according to the present application.
3 shows a flowchart of a first embodiment of an automatic classification method according to the present application.
4 shows a flowchart of a second embodiment of an automatic classification method according to the present application.
5 shows a block diagram of an embodiment of a device for determining a category directory according to the present application.
6 shows a block diagram of an embodiment of an automatic sorting device according to the present application.

Embodiments of the present disclosure provide a method and device for determining a category directory, and an automatic classification method and device.

DETAILED DESCRIPTION The following detailed description of technical solutions in the embodiments enables those of ordinary skill in the art to better understand the technical solutions herein by reference to the accompanying drawings, which form a part hereof. Apparently, the embodiments described herein merely represent some but not all of the present invention, and those skilled in the art will be able to derive other embodiments / examples from these embodiments without any creative efforts, and any of these And all are within the scope of this application.

In order to correctly classify resource processing records, an accurate category directory is required that will result in accurate classification results.

The following describes an embodiment of a method for determining a category directory according to the present application.

1 shows a flowchart of a first embodiment of a method for determining a category directory according to the present application. As shown in FIG. 1, the category directory determination method may include the following steps.

S101: The first category directory is determined based on the processing side information of the resource processing record and the preset first correspondence between the processing side information and the category.

The first category directory is determined based on the processing side information of the resource processing record and the preset first correspondence between the processing side information and the category. The processing side information may include a resource processing system name, a resource processing system characteristic, and the like, but is not limited thereto.

The first correspondence between the processing side information and the category may be preset.

The first correspondence may be determined based on the processing party information. The first correspondence may be determined based on the processing party associated with the processing side information and / or may be determined based on the characteristics of the processing party associated with the processing side information.

For example, the resource system A may include the subsystems a1 and a2, and in the first correspondence, the processing side information including the contents of a1 or a2 may all correspond to the category "A". In another example, resource system B and resource system C are both associated with a resource processing system for transportation. In the first correspondence, the processing side information including the content B or C may all correspond to the category "transport".

The first correspondence can also be determined based on keyword analysis of processing side information. For example, if the processing side information includes "singer A's song", keyword analysis of the processing side information may indicate that both "singing" and "singer A" belong to the music domain. Therefore, a correspondence can be established between the processing side information of "Singer A's song" and the category "Music".

In the first correspondence, one or more processing side information may correspond to a single category.

The first category directory may be determined based on the first correspondence between the processing side information included in the resource processing record and the category. The first category directory may include category identifiers (“category IDs”) and associated category names of one or more categories. The category directory may also include a first correspondence between processing side information and the category.

S102: Receive a category change message from the user, and generate a category change item containing the category change contents.

The category directory determining device may receive a category change message from the user. The category change message indicates changing the category of the resource processing record. Such a category change message includes a user identifier ("user ID"), processing side information contained in the resource processing record, category change time, category ID before change ("category ID before change"), and category ID after change ("after change"). Category ID "). Such a user category change message may be generated automatically when the user modifies the category classification and sent to the category directory determination device.

The category directory determining device may generate a category change item based on the received category change message. The category change item may include category change contents, a user ID, and a category change time. The category change content may include processing side information, category ID before change, and category ID after change.

S103: Determine a statistical start time associated with the first category ID included in the category change item, and determine a first time interval associated with the first category ID.

The category directory determining device may determine a statistical start time associated with the first category ID included in the category change item. The first category ID may be one of the category IDs before the change in the category change.

The determination of the statistical start time associated with the first category ID may include setting, as the statistical start time, a point in time immediately before the first category ID is modified in the related category directory to which the first category ID belongs.

The operation of determining the statistical start time may be performed repeatedly at preset time intervals. The preset time interval may be preset by the user using the category directory determination device.

The first time interval associated with the first category ID may be determined based on the determined statistical start time. Specifically, for example, a period between the statistical start time and the current time may be taken at the first time interval associated with the first category ID.

S104: Statistically analyze the category change item generated within the first time interval and including the first category ID to obtain a first statistical analysis result.

The category directory determining device may statistically analyze the category change item generated within the first time interval and including the first category ID to obtain a first statistical analysis result. Specifically, for example, the statistical analysis may obtain, as the first total amount, the total number of first candidate category change items each including a pre-change category ID equal to the first category ID. The second total amount may be obtained as the total number of user ID types included in the first candidate category change item. The statistical analysis may also obtain, as a third total amount, the total number of second candidate category change items, each of which is among the first candidate category change items and further includes a post-change category ID equal to the second category ID. The fourth total amount may be obtained as the total number of user ID types included in the second candidate category change item. The second category ID is different from the first category ID.

The first statistical analysis result may include a first total amount, a second total amount, a third total amount, and a fourth total amount.

In an illustrative example, the first category ID may be "A" and the second category ID may be "B". The statistical analysis may identify all category change items each including the category ID "A" before the change as the first candidate category change item. The total number of first candidate category change items is obtained as the first total amount. The total number of user ID types included in the first candidate category change item may be obtained as the second total amount. The statistical analysis may identify all first candidate category change items each including category ID "B" after the change as the second candidate category change item. The total number of second candidate category change items may be obtained as the third total amount. The total number of user ID types included in the second candidate category change item may be obtained as the fourth total amount.

S105: When the first statistical analysis result satisfies the first preset rule, change the first category directory including the first correspondence to the second category directory including the second correspondence between the processing side information and the category. And setting the second category directory as the default category directory, and setting the first category directory as the default category directory when the first statistical analysis result does not satisfy the first preset rule.

The first statistical analysis result may be compared with the first preset rule. The first preset rule can be used to determine whether the first category directory and the first correspondence should be modified.

The first preset rule is the following rule,

The first total amount of the first statistical analysis result is greater than or equal to the first preset threshold, the first preset threshold being less than or equal to the total number of category change items generated within the first time interval,

The second total amount of the first statistical analysis result is greater than or equal to the second preset threshold, the second preset threshold is less than or equal to the total number of user ID types in the category change item generated within the first time interval, and 2 preset threshold is less than or equal to the first total amount,

The third total amount of the first statistical analysis result is greater than or equal to the third preset threshold, and the third preset threshold is less than or equal to the first total amount,

The fourth total amount of the first statistical analysis result is greater than or equal to the fourth preset threshold, and the fourth preset threshold is less than or equal to the third total amount.

It may include one or more of.

If the first statistical analysis result satisfies the first preset rule, the first correspondence may be modified such that the processing side information previously corresponding to the first category ID under the first correspondence now corresponds to the second category ID. Can be. Therefore, the second correspondence relationship is generated through the modification of the first correspondence relationship. The second category directory may be created based on the second correspondence. The second category directory may include one or more category IDs and a second correspondence between the one or more category IDs and the processing side information. The second category directory may be set as the default category directory.

If the first statistical analysis result does not satisfy the first preset rule, the first category directory including the first correspondence will not be modified and may be set as a default category directory.

The default category directory can be used as the final determined category directory according to embodiments herein.

In the first embodiment of the above-described method for determining the category directory, the correspondence between the processing side information and the category is determined based on the analysis of the processing side information, so that similar resource processing records are classified into the same category. . Thus, category directories determined using this method will result in improved accuracy of the classification results. On the other hand, the existing category directory will be constantly updated based on the received user category change message, which ensures that the generated category directory meets user needs. This in turn improves the accuracy of the classification results.

2, a second embodiment of a method of determining a category directory is described. 2 shows an exemplary flow diagram of a second embodiment of a method for determining a category directory. As shown in FIG. 2, compared to the first embodiment shown in FIG. 1, the second embodiment of the method for determining the category directory includes the following operations.

S106: Statistically analyze the category change item generated within the first time interval with respect to the user and including the third category ID, to obtain a second statistical analysis result.

The category change item of the individual user in the first time interval may be statistically analyzed to identify the item including the third category ID. The second statistical analysis result can be obtained.

Specifically, for example, the statistical analysis may identify a third candidate category change item that is generated with respect to a particular user within the first time interval and includes a pre-change category ID that is the same as the third category ID. The total number of third candidate category change items may be obtained as the fifth total amount. In addition, the statistical analysis may identify the fourth candidate category change item further including a category ID after the same change as the fourth category ID among the third candidate category change items. The total number of fourth candidate category change items may be obtained as the sixth total amount. The third category ID and the fourth category ID may be pre-change category ID and post-change category ID included in the category change message received from the specific user, respectively.

The second statistical analysis result may include a fifth total amount and a sixth total amount.

S107: If the second statistical analysis result satisfies the second preset rule, change the second category directory including the second correspondence to the third category directory including the third correspondence between the processing side information and the category. And setting the third category directory as a user category directory associated with the user.

The second statistical analysis result may be compared with the second preset rule. The second preset rule can be used to determine whether the second category directory and the second correspondence need to be modified.

The second preset rule is the following rule,

The fifth total amount of the second statistical analysis result is greater than or equal to the fifth preset threshold, and the fifth preset threshold is greater than the total number of category change items generated within the first time interval when a category change message is received from the user. Less than or equal to,

The sixth total amount of the second statistical analysis result is greater than or equal to the sixth preset threshold and the sixth preset threshold is less than or equal to the fifth total amount.

It may include one or more of.

If the second statistical analysis result satisfies the second preset rule, the second correspondence may be modified such that the processing side information previously corresponding to the third category ID under the second correspondence now corresponds to the fourth category ID. Can be. Therefore, the third correspondence is generated through the modification of the second correspondence. The third category directory may be created based on the third correspondence. The third category directory may include one or more category IDs and a third correspondence between the one or more category IDs and the processing side information. The third category directory may be set as a user category directory associated with the user.

If the second statistical analysis result does not satisfy the second preset rule, no user category directory will be set for the user.

In addition to the default category directory determined by the first embodiment of the method for determining the category directory, the above-described second embodiment can determine a user category directory associated with a particular user, which is one that meets user needs and classifies accuracy. It also ensures that this is improved.

An example scenario of determining an accounting category can be used to further describe the aforementioned methods for determining a category directory.

In an example scenario, the information of merchant "A" is merchant name "A", women's wear, the information of merchant "B" is merchant name "B", ceramic tile, and the information of merchant "C" is merchant name "C". The information of the merchant "D" may include a merchant name "D", a taxi reservation software development company, and the information of the merchant "E" may include a merchant name "E", "a song of the singer A".

Based on the first correspondence, an accounting category for each merchant can be determined. For example, under the first correspondence, merchant "A" may correspond to category "clothing", merchant "B" may correspond to category "household decoration", and merchant "C" to category "household decoration". May correspond, merchant "D" may correspond to category "transport", and merchant "E" may correspond to category "music". Table 1 below shows the correspondence between merchants and categories.

The accounting category of Table 1 may be a first accounting category directory.

If the user is not satisfied with the accounting category in the first accounting category directory, the user can modify the accounting category in the accounting operation. The category directory determining device may receive a message indicating that the user has changed the accounting category. For example, the user category change message may include the user '1', the merchant 'B', January 1, 2014, the category 'home decoration' before the change, and the category 'building material' after the change. Based on the user category change message, a category change item may be generated. The category change item may include "B_household decoration_building material", "1", and "20140101", where "B_household decoration_building material" may be the content of an accounting category change. Similarly, multiple user category change messages may be received from this user "1" and / or other users, and correspondingly, multiple category change items will be generated.

First, a statistical start time associated with a first category ID included in a category change item may be determined. For example, when the first category ID is "home decoration", a time point immediately before the first category ID "home decoration" is changed, for example, May 1, 2013 may be used as the statistical start time. Assuming that the current date is April 30, 2014, the first time interval may be determined as a period from May 1, 2013 to April 30, 2014.

Within the first time interval (May 1, 2013 through April 30, 2014), there are 50000 category change items each containing the category "home decoration" before each change (ie, the first Total amount is 50000). Among the 50000 category change items, there are 40000 user ID types (ie, the second total amount is 40000). Among the 50000 category change items, there are 45000 category change items each including the category "building material" after the change (that is, the third total amount is 45000). Among the 45,000 category change items, there are 30000 user ID types (ie, the fourth total amount is 30000).

The first preset rule to be assumed includes that the third total amount is greater than or equal to 40,000 and the fourth total amount is greater than or equal to 20000. Thus, the first statistical result satisfies the first preset rule. Thus, the first correspondence between merchant "B" and the accounting category "home decoration" is changed to the second correspondence between merchant "B" and the accounting category "building material". The second correspondence between merchants and accounting categories is shown in Table 2 below.

The accounting category of Table 2 may be a second accounting category directory.

To address a user's specific needs, a custom accounting category directory can be created for the user. For example, a statistical analysis could be made for category change entries that were created for user "1" during the first time interval (May 1, 2013-April 30, 2014) and include the category "Home decoration" before the change. Can be identified. The total amount of such category change items (eg 1000) may be the fifth total amount. Of the 1000 category change items, 800 include the category "Furniture" after the change. Therefore, the sixth total amount is 800. The second statistical analysis result includes the fifth total amount 1000 and the sixth total amount 800.

The second preset rule to be assumed may include that the fifth total amount is greater than or equal to 800 and the sixth total amount is greater than or equal to 600. Thus, the second statistical analysis result satisfies the second preset rule. Thus, the correspondence between merchant "C" and the accounting category "home decoration" can be changed to the correspondence between merchant "C" and the accounting category "furniture". The third correspondence between merchants and accounting categories is shown in Table 3 below.

The accounting category of Table 3 may be a user accounting category directory. The user accounting category directory is customized for user "1" and is used only for accounting records related to user "1".

Hereinafter, an embodiment of the automatic classification method will be described.

3 shows an exemplary flowchart of a first embodiment of an automatic classification method. The class classification method illustrated in FIG. 3 may use the category directory determined according to the first embodiment of determining the category directory illustrated in FIG. 1. The automatic classification method may include the following operations.

S301: Receive a resource processing record from the user. The resource processing record sent by the user may be received. The resource processing record may include a user ID, processing side information, resource amount, resource processing time, and other information.

S302: Classify the received resource processing record based on the second correspondence between the category included in the default category directory and the processing side information to obtain a classification result. The processing side information may be obtained from the resource processing record, and the second correspondence may be obtained using the first embodiment of the method for determining the category directory. Then, the resource processing record may be classified based on the second correspondence between the obtained processing side information and the default category directory to obtain a classification result.

S303: Return the classification result to the user.

4 shows an exemplary flowchart of a second embodiment of an automatic classification method. The automatic classification method shown in FIG. 4 may use the category directory determined according to the second embodiment of determining the category directory shown in FIG. 2. The automatic classification method may include the following operations.

S401: Receive a resource processing record from the user. The resource processing record sent by the user may be received. The resource processing record may include a user ID, processing side information, resource amount, resource processing time, and other information.

S402: Query whether a user category directory associated with a user exists. If such a user category directory exists, the received resource processing record is classified based on the third correspondence between the category included in the user category directory and the processing side information to obtain a classification result. Such user category directory and third correspondence have priority over the default category directory at the time of classification.

S403: If there is no user category directory associated with the user, classify the received resource processing record based on the second correspondence between the category included in the default category directory and the processing side information to obtain a classification result.

S404: Return the classification result obtained to the user based on the user category directory or based on the default category directory.

The above-described second embodiment of the automatic classification method corresponds to the second embodiment of the method for determining the category directory. Such a classification method can generate more accurate classification results, and can perform a classification operation using a user specific category directory customized so that the obtained classification results meet the classification needs of a specific user.

An embodiment of the category directory determination device will be described below.

5 shows a block diagram of an embodiment of a category directory determination device. As shown in FIG. 5, the category directory determination device includes a first category directory determination unit 501, a category change item generation unit 502, a first time interval determination unit 503, and a first statistical analysis. Unit 504 and a default category directory determination unit 505.

The first category directory determination unit 501 may be operable to determine a first category directory based on the processing side information of the resource processing record and a preset first correspondence between the processing side information and the category.

The category change item generating unit 502 may be operable to receive a category change message from a user and generate a category change item including the contents of the category change message.

The first time interval determination unit 503 is configured to determine a statistical start time associated with the first category ID included in the category change item, and determine a first time interval associated with the first category ID based on the statistical start time. can do .

The first statistical analysis unit 504 may be operable to statistically analyze the category change item generated within the first time interval and including the first category ID to obtain a first statistical analysis result.

When the first statistical analysis result satisfies the first preset rule, the default category directory determination unit 505 sets the second category relationship between the processing side information and the category as the first category directory including the first relationship. Change to the containing second category directory and set the second category directory as the default category directory, and if the first statistical analysis result does not satisfy the first preset rule, set the first category directory as the default category directory. It can work.

In addition, the category directory determination device may also include a second statistical analysis unit 506 and a user category directory determination unit 507.

The second statistical analysis unit 506 may be operable to statistically analyze the category change item generated in association with the user within the first time interval and including the third category ID to obtain a second statistical result.

The user category directory determination unit 507 may, when the second statistical analysis result satisfies the second preset rule, convert the second category directory including the second correspondence into the third category directory including the third correspondence. To operate. The third category directory may be set as a user category directory for the user.

The category directory determination device may be associated with an embodiment of a method for determining a category directory to implement a method for determining a category directory to achieve a desired technical effect.

6 shows a block diagram of an embodiment of an automatic classification device. As shown in FIG. 6, the automatic classification device may include a receiving unit 601, a default category classification unit 602, and a feedback unit 603.

The receiving unit 601 may be operable to receive a resource processing record from a user.

The default category classification unit 602 may operate to classify the resource processing record using the second correspondence between the category included in the default category directory and the processing side information to obtain a classification result.

The feedback unit 603 may be operable to return the classification result to the user.

In addition, the automatic classification device may also include a user specific classification unit 604.

The user specific classification unit 604 may be operative to query whether a user category directory associated with the user of the received resource processing record exists. If such a user category directory exists, the user specific classification unit 604 classifies the received resource processing record based on the third correspondence between the category included in the user category directory and the processing side information to obtain a classification result. will be. The classification result will be returned to the user via the feedback unit 603. If no such user category directory associated with the user exists, the user specific classification unit 604 will transfer the manipulation of the classification to the default category classification unit 602.

Embodiments of the above-described automatic classification device may be associated with embodiments of the automatic classification method when implementing the automatic classification method to obtain the expected technical effect.

In the 1990s, improvements in technology can be clearly distinguished as improvements in hardware (e.g., improvements in circuit design such as diodes, transistors, switches, etc.) or improvements in software (e.g., improved process flows). However, with the development of technology, improvements of many method processes have been regarded as direct improvements of hardware circuit structure nowadays. In most cases, designers embed the improved method process flow into hardware circuitry to obtain the hardware circuit structure. Thus, the idea that an improvement in process flow cannot be achieved in a hardware module is unfounded. For example, a programmable logic device (PLD) such as a field programmable gate array (FPGA) is an integrated circuit whose logic function is determined by a user through programming. Designers program PLDs to integrate digital systems into PLDs without requiring chip manufacturers to design and manufacture dedicated integrated circuit chips. In addition, such "chip programming" can be accomplished through logic compiler software similar to the software compiler used for software development. The original code before compilation can be written in a specific programming language called a hardware description language (HDL). HDL includes Advanced Boolean Expression Language (ABEL), Altera Hardware Description Language (AHDL), Confluence, Cornell University Programming Language (CUPL), HDCal, Java Hardware Description Language (JHDL), Lava, Laura (Lola), MyHDL, PALASM, Ruby Hardware Description Language (RHDL), and the like. Currently used HDLs include Very High-Speed Integrated Circuit Hardware Description Language (VHDL) and Verilog2. Those skilled in the art will clearly understand that a hardware circuit can implement a logic process flow by programming / embedding the logic process flow onto an integrated circuit using some of the hardware description languages described above.

The controller can be implemented in any suitable manner. For example, the controller may be configured via instructions, logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers executable by a microprocessor or processor and a microprocessor / processor stored on a computer readable medium. Can be implemented. Examples of controllers include, but are not limited to, ARC 625D, Atmel AT9SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. The memory controller may also be implemented as part of the control logic of the memory.

Those skilled in the art will also recognize that in addition to implementing the controller in a pure computer readable program code manner, the controller may be implemented through logic gates, switches, special integrated circuits, programmable logic controllers, and / or embedded microcontrollers. will be. Thus, such a controller can be considered a hardware component, and the units can be regarded as the structure of a hardware component. Also, such units may be considered as software modules and hardware structures for achieving functionality.

The system, device, module, or unit described above may be implemented by a computer chip or system or by a product having a particular function.

For convenience of description, the devices are described in various units in terms of functionality. Of course, one or more functions of the units may be implemented together in one or more software and / or hardware elements when implementing the present application.

It will be apparent to those skilled in the art that the present application may be implemented by software and a necessary general purpose hardware platform. Based on this understanding, technical advance contributions made to the technical solutions or techniques of this application may be implemented in the form of software products. In a typical configuration, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory. The software product may include specific instructions for enabling / configuring the computing device (which may be a personal computer, server, or network device) to implement some of the methods or methods described in the embodiments of the present application. The computer software product can be stored in memory. The memory may include computer readable media including volatile memory, random access memory (RAM) and / or nonvolatile memory such as read only memory (ROM) or flash RAM. Memory is an example of computer storage / computer readable media, including removable and non-removable media, and can be implemented by any method or technology of information storage. The information may be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include phase change memory (PCM), static random access memory (SRAM), dynamic random access memory (DRAM), and other types of random access memory (RAM), read-only memory (ROM), and EEPROM. (electrically erasable programmable read-only memory), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disk (DVD) and other optical storage devices, magnetic cassettes, magnetic tape / magnetic disk storage Apparatus or other magnetic storage device, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer storage media / readable media does not include transitory computer readable media, such as modulated data signals and carriers.

Various embodiments herein are described in a stepwise manner. Where similarities exist between the different embodiments, reference may be made between such embodiments for understanding. Differences between the embodiments can be explained. For example, with respect to system embodiments, reference may be made to method embodiments to understand the disclosure.

The present application relates to personal computers (PCs), servers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers It may be used in a number of general purpose or special purpose computer system environments or configurations, such as distributed computing environments, which may include any of the above computing systems or devices.

The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like, that can perform particular tasks and / or implement particular abstract data types. The present application can also be implemented in a distributed computing environment. In a distributed computing environment, work is performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and / or remote computer storage media including storage devices.

While the present application has been described by way of some exemplary embodiments, those skilled in the art will understand that other variations exist without departing from the spirit and scope of the present application, and the appended claims are intended to cover such modifications and terms without departing from the spirit and scope of the present application. It will be expected to include modifications.

Claims (19)

A method for determining a category directory, performed by a computer, comprising:
Determining a first category directory based on processing side information of a resource processing record and a first predetermined correspondence relationship between the processing side information and a category;
Receiving a category change message from a user, generating a category change item including category change contents indicating that the user changes a first category having a first category ID to a second category having a second category ID; ,
Determining a statistical start time associated with the first category ID included in the category change item, and determining a first time interval associated with the first category ID based on the statistical start time;
Statistically analyzing a category change item generated within the first time interval and including the first category ID to obtain a first statistical analysis result;
If the first statistical analysis result satisfies a first preset rule, modifying the first category directory including the first correspondence to include a second correspondence between the processing side information and a category; Obtaining a category directory and setting the second category directory as a default category directory;
If the result of the first statistical analysis does not satisfy the first preset rule, setting the first category directory as a default category directory;
How to determine the category directory.
The method of claim 1,
The first correspondence between the processing side information and the category analyzes the processing side information including a processing party associated with the processing side information, characteristics of the processing party, or a keyword included in the processing side information. Determined based on
How to determine the category directory.
The method of claim 1,
The first correspondence relationship includes one or more processing side information corresponding to a category.
How to determine the category directory.

The method of claim 1,
The category directory includes a category ID of at least one category, a category name associated with the category ID, and the first correspondence between the processing side information and the at least one category.
How to determine the category directory.
The method of claim 1,
The category change message includes a user ID, processing side information of an associated resource processing record, a time of a category change event, a category ID before change and a category ID after change.
How to determine the category directory.
The method of claim 1,
The category change item includes a category change content, a user ID, and a time of a category change event, respectively,
The category change content includes processing side information of an associated resource processing record, a category ID before change, and a category ID after change.
How to determine the category directory.
The method of claim 1,
Statistically analyzing the category change item generated within the first time interval and including the first category ID,
Statistically analyzing a first total amount of a first candidate category change item each including a pre-change category ID equal to the first category ID;
Statistically analyzing a second total amount of a user ID type associated with the first candidate category change item;
Statistically analyzing a third total amount of a second candidate category change item each including a post-change category ID equal to the second category ID;
Statistically analyzing a fourth total amount of a user ID type associated with the second candidate category change item
How to determine the category directory.
The method of claim 7, wherein
The first statistical analysis result includes the first total amount, the second total amount, the third total amount and the fourth total amount.
How to determine the category directory.
The method of claim 7, wherein
The first preset rule,
The first total amount is greater than or equal to a first preset threshold, and wherein the first preset threshold is less than or equal to the total number of category change items generated within the first time interval,
The second total amount is greater than or equal to a second preset threshold, the second preset threshold is less than or equal to the total number of user ID types in a category change item generated within the first time interval, and the second preset The set threshold is less than or equal to the first total amount,
The third total amount is greater than or equal to a third preset threshold, and the third preset threshold is less than or equal to the first total amount,
The fourth total amount is greater than or equal to a fourth preset threshold and the fourth preset threshold is less than or equal to the third total amount.
Containing at least one of
How to determine the category directory.

The method of claim 1,
Statistically analyzing a category change item generated within the first time interval with respect to a user and including a third category ID to obtain a second statistical analysis result;
And when the second statistical analysis result satisfies a second preset rule, modifying the second category directory including the second correspondence to include a third correspondence between the processing side information and the category. Obtaining a third category directory, and setting the third category directory as a user category directory for the user;
How to determine the category directory.
The method of claim 10,
Statistically analyzing a category change item generated within the first time interval with respect to the user and including a third category ID,
Statistically analyzing a fifth total amount of third candidate category change items each including a pre-change category ID equal to the third category ID;
Statistically analyzing a sixth total amount of a fourth candidate change category item, each of which is present among the third candidate category change items and includes a category ID after change that is equal to a fourth category ID
How to determine the category directory.
The method of claim 11,
The second statistical analysis result includes the fifth total amount and the sixth total amount.
How to determine the category directory.
The method of claim 11,
The second preset rule,
The fifth total amount is greater than or equal to a fifth preset threshold, and wherein the fifth preset threshold is less than or equal to the total number of category change items generated within the first time interval with respect to the user,
The sixth total amount of the second statistical analysis result is greater than or equal to a sixth preset threshold and the sixth preset threshold is less than or equal to the fifth total amount.
Containing at least one of
How to determine the category directory. An automatic classification method performed by a computer, which classifies using a category directory determined by a category determination method,
Receiving a resource processing record from a user,
Classifying the received resource processing record based on a second correspondence between a category in a default category directory and processing side information;
Returning a classification result to the user.
Automatic classification method.
The method of claim 14,
When receiving the resource processing record from the user,
Querying whether a user category directory associated with the user exists;
If there is a user category directory associated with the user, classifying the received resource processing record based on a third correspondence between a category included in the user category directory and processing side information to obtain a classification result;
If the user category directory associated with the user does not exist, classifying the received resource processing record based on a second correspondence between a category included in a default user category directory and processing side information to obtain a classification result; More containing
Automatic classification method.
As a category directory determination device,
A first category directory determination unit, a category change item generation unit, a first time interval determination unit, a first statistical analysis unit, and a default category directory determination unit,
The first category directory determining unit is operable to determine a first category directory based on processing side information of a resource processing record and a preset first correspondence between the processing side information and a category,
The category change item generating unit receives a category change message from a user, and includes a category change item including category change contents indicating to change a first category having a first category ID to a second category having a second category ID. Is operable to generate
The first time interval determining unit determines a statistical start time associated with the first category ID included in the category change item, and determines a first time interval associated with the first category ID based on the statistical start time. Is operable to
The first statistical analysis unit is operable to statistically analyze a category change item generated within the first time interval and including the first category ID to obtain a first statistical analysis result,
The default category directory determining unit is configured to generate a second correspondence between processing side information and a category in the first category directory including the first correspondence when the first statistical analysis result satisfies the first preset rule. Change to a second category directory that includes and set the second category directory as the default category directory, and if the first statistical analysis result does not satisfy the first preset rule, set the first category directory to a default category directory Operable to set as
Category directory determination device.
The method of claim 16,
Further comprising a second statistical analysis unit and a user category directory determining unit,
The second statistical analysis unit is operable to statistically analyze a category change item generated within the first time interval with respect to a user and including a third category ID to obtain a second statistical analysis result,
The user category directory determining unit, when the second statistical analysis result satisfies a second preset rule, changes the second category directory including the second correspondence to generate a third between the processing side information and the category. Obtain a third category directory containing a correspondence and set the third category directory as a user category directory for the user
Category directory determination device.
As an automatic sorting device,
Including a receiving unit, a default category classification unit and a feedback unit,
The receiving unit is operable to receive a resource processing record from a user,
The default category classification unit is operable to classify the resource processing record using a second correspondence between a category included in a default category directory and processing side information to obtain a classification result,
The feedback unit is operable to return the classification result to the user.
Automatic sorting device.
The method of claim 18,
Further include user specific classification units,
The user specific classification unit,
Query whether the user category directory associated with the user sending the resource processing record exists,
If a user category directory associated with the user exists, classifying the received resource processing record based on a third correspondence between a category included in the user category directory and processing side information to obtain a classification result, and classifying Feedback the results to the user,
If there is no user category directory associated with the user, transferring the received resource processing record to the default category classification unit.
Automatic sorting device.

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